Is it time to throw out the creative director and rely on big data to predict what consumers want to wear next? Assistant Professor Ayelet Israeli discusses how Gap CEO Art Peck considers this bold idea to boost sales.
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Passengers arriving at international hubs often endure delays, especially at immigration and security. This study of London’s Heathrow Airport develops a system to provide real-time information about transfer passengers’ journeys through the airport to better serve passengers, airlines, and their employees. It shows how advanced machine learning could be accessible to managers.

Corporate finance researchers who analyze patent data are at risk of making highly predictable errors. The problem arises from dramatic changes in the direction and location of technological innovation (and patenting practice) over recent decades. This paper explains the pitfalls and suggests practical steps for avoiding them.

Personal selling in the form of detailing to physicians is the main go-to-market practice in the pharmaceutical industry. This paper provides a practical framework to analyze the effectiveness of detailing efforts. The method and empirical insights can help firms allocate sales-force resources more efficiently and devise optimal routes and call-pattern designs.

Contemporary business environments are constantly evolving, requiring continual changes to the software applications that support a business. Moreover, during recent decades, the sheer number of applications has grown significantly, and they have become increasingly interdependent. Many companies find that managing applications and implementing changes to their application portfolio architecture is increasingly difficult and expensive. Firms need a way to visualize and analyze the modularity of their software portfolio architectures and the degree of coupling between components. In this paper, the authors test a method for visualizing and measuring software portfolio architectures using data of a biopharmaceutical firm's enterprise architecture. The authors also use the measures to predict the costs of architectural change. Findings show, first, that the biopharmaceutical firm's enterprise architecture can be classified as core-periphery. This means that 1) there is one cyclic group (the "Core") of components that is substantially larger than the second largest cyclic group, and 2) this group comprises a substantial portion of the entire architecture. In addition, the classification of applications in the architecture (as being in the Core or the Periphery) is significantly correlated with architectural flexibility. In this case the architecture has a propagation cost of 23 percent, meaning almost one-quarter of the system may be affected when a change is made to a randomly selected component. Overall, results suggest that the hidden structure method can reveal new facts about an enterprise architecture. This method can aid the analysis of change costs at the software application portfolio level. Key concepts include: This method for architectural visualization could provide valuable input when planning architectural change projects (in terms of, for example, risk analysis and resource planning). The method reveals a "hidden" core-periphery structure, uncovering new facts about the architecture that could not be gained from other visualization procedures or standard metrics. Compared to other measures of complexity, coupling, and modularity, this method considers not only the direct dependencies between components but also the indirect dependencies. These indirect dependencies provide important input for management decisions.
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In their new book Keeping Up with the Quants, Thomas H. Davenport and Jinho Kim offer tools to sharpen quantitative analysis and make better decisions. Read our excerpt.
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Poring over reader responses to his May column, HBS professor Jim Heskett is struck by the fact that they include behavioral, structural, and even mechanical remedies. (Forum now closed. Next forum opens June 3.)
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What difference do angel investors make for the success and growth of new ventures? William R. Kerr and Josh Lerner of HBS and Antoinette Schoar of MIT provide fresh evidence to address this crucial question in entrepreneurial finance, quantifying the positive impact that angel investors make to the companies they fund. Angel investors as research subjects have received much less attention than venture capitalists, even though some estimates suggest that these investors are as significant a force for high-potential start-up investments as venture capitalists, and are even more significant as investors elsewhere. This study demonstrates the importance of angel investments to the success and survival of entrepreneurial firms. It also offers an empirical foothold for analyzing many other important questions in entrepreneurial finance. Key concepts include: Angel-funded firms are significantly more likely to survive at least four years (or until 2010) and to raise additional financing outside the angel group. Angel-funded firms are also more likely to show improved venture performance and growth as measured through growth in Web site traffic and Web site rankings. The improvement gains typically range between 30 and 50 percent. Investment success is highly predicated by the interest level of angels during the entrepreneur's initial presentation and by the angels' subsequent due diligence. Access to capital per se may not be the most important value-added that angel groups bring. Some of the "softer" features, such as angels' mentoring or business contacts, may help new ventures the most.
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We all should learn from failure—but it's difficult to do so objectively. In this excerpt from "Failing to Learn and Learning to Fail (Intelligently)" in Long Range Planning Journal, HBS professor Amy Edmondson and coauthor Mark Cannon offer a process for analyzing what went wrong.
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